Python Developer
Summary
Senior Python Engineer at a technology firm building an AI-powered engineering simulation platform. Day to day: design and scale cloud-native backends, data-intensive pipelines, and APIs powering high-performance simulation and AI-driven workflows, plus code reviews, architecture, and mentoring. Core stack: Python, cloud platforms, containers.
We are partnering with an innovative technology business operating at the intersection of software engineering, artificial intelligence, and advanced computational modelling. Our client is building next-generation platform solutions that drastically accelerate engineering analysis and design processes across a range of industrial sectors.
They are looking for a Senior Python Engineer who is a problem-solver at heart and excited by deep technical challenges. In this hands-on role, you will help design, build, and scale platform capabilities that power high-performance simulation workflows, data-intensive pipelines, and AI-driven applications.
What You Bring
- Python Expertise: 4+ years of commercial software engineering experience with strong proficiency in Python and modern development practices.
- Cloud Experience: Solid background building full-stack or backend applications using cloud platforms and containerisation technologies.
- Design & Architecture: Proven ability to work with large-scale data processing systems and contribute to architectural decision-making.
- Communication & Collaboration: Excellent communication skills with experience partnering across multidisciplinary teams of software engineers, data specialists, and domain experts.
- AI-powered engineering tools
Nice to have:
- Scientific Computing: Familiarity with scientific libraries like Pytorch, NumPy, or visualisation tools like Matplotlib, plotly,..
- CFD
Key Responsibilities
- Platform Architecture & Backend: Design and scale cloud-native backend systems, ensuring high reliability, performance, and long-term extensibility.
- Cloud & Infrastructure: Drive cloud-native best practices across resiliency, observability, security, containerisation, and deployment strategies.
- Integrations & APIs: Develop robust APIs to integrate external modelling tools, third-person applications, and complex data sources.
- Technical Leadership & Quality: Set high engineering standards, conduct code reviews, participate in architecture discussions, and mentor junior engineers.
- Exposure to scientific computing, numerical methods, machine learning tooling, or computational workloads.
- Familiarity with engineering software, simulation tools, or 3D/CAD environments
If this sounds like the right challenge, let's talk